Graduate Course Instruction Modes and Registration Information

Graduate Course Offerings for Spring 2021

The Courant Computer Science department designed our spring 2021 offerings, following university and GSAS guidance, and state and city health and safety guidelines. Each section received an instruction mode designation.

  • Online: Faculty and all students are remote; there is no physical classroom.
  • Blended: The section or an associated activity (tutorials or project sessions) are partially in-person with rotation of in-person and remote attendance.
  • In-Person: The section is in-person with ordinary meetings.

Regardless of the instruction mode, students will have an option to attend entirely remotely for all courses.

A list of graduate-level courses for each mode can be found below. This list is up-to-date as of December 18, 2020. Course designations may be revised based on the guidance we get from the university. We will inform all registered students promptly if a course designation changes.

For some courses, the in-person component structure and scheduling is not finalized yet; additional information will be posted on the course web pages and in Albert.


The instruction mode for the following courses is blended lecture unless noted otherwise.

  • CSCI-GA.1170-001 Fundamental Algorithms (lecture fully online)
    • CSCI-GA.1170-002 Fundamental Algorithms Recitation (online)
    • CSCI-GA.1170-003 Fundamental Algorithms Recitation (blended)
  • CSCI-GA.1180-001 Mathematical Techniques For CS Applications (blended)
  • CSCI-GA.2110-001 Programming Languages (lecture fully online)
    • CSCI-GA.2110-002 Programming Languages Recitation (online)
    • CSCI-GA.2110-003 Programming Languages Recitation (blended)
  • CSCI-GA.2250-001 Operating Systems (blended)
  • CSCI-GA.2250-002 Operating Systems (blended)
  • CSCI-GA.2433-001 Database Systems (blended)
  • CSCI-GA.3840-001 Master’s Thesis Research
  • CSCI-GA.3860-001 PhD Thesis Research


  • CSCI-GA.1144-001 PAC II
    • CSCI-GA.1144-002 PAC II Recitation
  • CSCI-GA 2130-001 Compiler Construction
  • CSCI-GA.2262-001 Data Communications and Networks
  • CSCI-GA.2270-001 Computer Graphics
  • CSCI-GA.2421-001 Numerical Methods II
  • CSCI-GA.2437-001 Big Data Application Development
  • CSCI-GA.2440-001 Software Engineering
  • CSCI-GA.2520-001 Bioinformatics and Genomes
  • CSCI-GA.2560-001 Artificial Intelligence
  • CSCI-GA.2565-001 Machine Learning
  • CSCI-GA.2572-001 Deep Learning
  • CSCI-GA.2620-001 Networks and Mobile Systems
  • CSCI-GA.2820-001 DevOps and Agile Methodologies
    • CSCI-GA.2820-002 DevOps and Agile Methodologies Lab
  • CSCI-GA.2945-002 Adv Topics in Num Analysis: High Performance Computing
  • CSCI-GA.2945-003 Adv Topics in Num Analysis: Immersed Boundary Methods
  • CSCI-GA.2945-004 Adv Topics in Num Analysis: Stochastic Modeling and Uncertainty Quantification
  • CSCI-GA.3033-004 Special Topics: Statistical Natural Language Processing
  • CSCI-GA.3033-026 Special Topics: Cloud Computing
  • CSCI-GA.3033-029 Special Topics: Social Networks
  • CSCI-GA.3033-034 Special Topics: Multicore Processors: Architecture and Processing
  • CSCI-GA.3033-052 Special Topics: Advanced Machine Learning
  • CSCI-GA.3033-059 Special Topics: Big Data Science
  • CSCI-GA.3033-071 Special Topics: Geometric Modeling
  • CSCI-GA.3033-074 Special Topics: Practical Computer Security
  • CSCI-GA.3033-076 Special Topics: Vision Meets Machine Learning
  • CSCI-GA.3033-077 Special Topics: Big Data and ML Systems
  • CSCI-GA.3033-078 Special Topics: Cryptocurrencies and Decentralized Ledgers
  • CSCI-GA.3033-079 Special Topics: Mathematics of Deep Learning
  • CSCI-GA.3033-085 Special Topics: Cloud and Machine Learning
  • CSCI-GA.3033-091 Special Topics: Introduction to Deep Learning Systems
  • CSCI-GA.3140-001 Abstract Interpretation
  • CSCI-GA.3812-001 Information Technology Projects  
  • CSCI-GA.3850-001 PhD Seminar: Cryptography
  • CSCI-GA.3850-004 PhD Seminar: Formal Methods


In light of the US travel restrictions due to the COVID-19 pandemic, Courant Computer Science department expects to offer the following NYU graduate computer science classes this spring in Shanghai at the NYU-Shanghai campus.

  • CSCI-GA.2110-011 Programming Languages
    • Instructors: Yuxin Deng and Jing Liu
  • CSCI-GA.2433-011 Database Systems
    • Instructor: Xiaoyang Sean Wang

Additional information on course offerings at NYUSH will be posted on this site once confirmed.

You can register for these classes directly in Albert. These classes will be held in person, and will have the same content and fulfill the same requirements as the corresponding courses at NYU-New York. These classes will commence the week of January 25, 2021.

Additionally, Courant Computer Science will offer courses jointly with the NYU Tandon School of Engineering in Shanghai. For MSCS students, these classes would count towards the 21 credits of standard graduate CS classroom-based courses. Additional information on course offerings at NYUSH will be posted on this site once confirmed.

  • CSCI-GA.3033-117/CS-GY 6033-SHAN Design and Analysis of Algorithms I
    • Instructor: Manuel Charlemagne
  • CSCI-GA.3033-256/CS-GY 6923-SHAN Machine Learning (lecture)
    • CSCI-GA.3033-SH1 Machine Learning (recitation)
    • CSCI-GA.3033-SH2 Machine Learning (recitation)
    • CSCI-GA.3033-SH3 Machine Learning (recitation)
      • Instructor: Bruno Abrahao


Update 10/11/2020: All international students who are newly enrolled as of Spring 2021 and hope to gain entry to the US for that term should be registered for at least one course during the semester that is not online. Acceptable courses are those whose instructional mode is listed in Albert as "In-Person," "Blended," or "Independent Studies." This restriction does *not* apply to international students whose enrollment is continuing from Spring 2020. Please contact the Office of Global Services (OGS) for international students for further guidance.